Workforce management is becoming an important factor in a company's ability to deliver projects, grow revenue and be more profitable. For successful delivery of labor-based project and services, the right people with the right skills should be available to provide services when needed. Forward-thinking businesses are investing in workforce optimization methodologies and solutions as a major competitive differentiator. The implementation of an advanced workforce optimization solution is a significant financial and time investment. Such implementation may include process development including the development of skill representation and taxonomies, staffing plans and project descriptions/templates; supporting IT infrastructure, e.g., the development of databases with employee and project information, as well as application development; and the development of advanced analytics to support different operations in the workforce management cycle, including forecasting the demand for resources/projects, capacity planning and optimization, and scheduling of resources/projects. Therefore, such investments are made over a longer period of time, typically several years. Consequently, process, infrastructure and algorithm designs are often made by different decision-makers, which frequently results in disconnects between the different components and elements of the system.
What is desirable, therefore, is a system and method for identifying quality, compatibility, reliability and other relevant issues related to various data in workforce management databases, which for example, may have been collected over a period of time and/or by different players.